tbuckley/cabot-search huggingface dataset:
OS05.7.A MICROLENS: EXPLORING THE GAP BETWEEN PATIENT AND CAREGIVER NEEDS, AND TECHNICAL DEVELOPMENTS IN AI-ENABLED MEDICAL IMAGE INTERPRETATION
Authors: L Pakzad-Shahabi, R Mauricaite, U Karamchandani, M Williams
Journal: Neuro-Oncology (2023)

Abstract BACKGROUND MicroLens aims to co-develop tools and functionality to enable patients &amp; caregivers to view and understand their own brain tumour images, using an explicit design-led approach. Over 7 months we used meetings, written reports and online questionnaires to capture the views of 20 staff, patient and caregiver participants requirements for an AI-enhanced online medical image viewing tool. We have described our initial approach and results (1), but here we focus on how patient and caregiver needs differ from technological approaches described in the medical imaging literature. MATERIAL AND METHODS As part of the MicroLens project, we used thematic analysis to extract key patient, caregiver and staff concerns and needs. We then compared this with technical themes of the medical imaging technical literature, drawn from conference proceedings (MICCAI). RESULTS The desired level of technical performance was relatively low: patients and caregivers would mostly be happy with labelling of common simple structures and sides, rather than detailed annotation. Other desirable functionality was around sharing imaging with family members and better understanding of imaging. In contrast, the technical literature had a focus on tumour segmentation, classification and prediction of outcomes - none of which appeared in patients' desiderata. CONCLUSION Patients, caregivers and staff want very different functionality than the work being conducted in the technical literature. The reasons for this are interesting, and multi-factorial, but reinforce the need for patient-led development. We are currently implementing a prototype and our software developers are designing and developing five of the key tools that emerged from MicroLens project, based on a combination of our findings and theoretical approaches such as the NASSS framework (2). (1) https://blogs.imperial.ac.uk/componc/2022/10/04/introducing-microlens-using-a-design-approach-to-understand-what-brain-tumour-patients-want-from-their-images/ (2)Greenhalgh T, et al A New Framework for Theorizing and Evaluating Nonadoption, Abandonment, and Challenges to the Scale-Up, Spread, and Sustainability of Health and Care Technologies J Med Internet Res 2017;19(11):e367
P18.08.B COMPARISON OF DOSE CALCULATION PLANNING SYSTEMS FOR RECCURENT MENENGIOMA TREATED WITH FRACTIONATED RE-IRRIDATION
Authors: Ç Hıdımoğlu, M Delikaya, S Hoca, Y Anacak, S Kamer
Journal: Neuro-Oncology (2023)

Abstract PURPOSE Meningioma is among the most common tumors of the central nervous system, accounting for approximately one-third of all brain tumors. Surgery is mainstay treatment and Radiotherapy (RT) provides long-term control in many patients, however recurrences following RT may occur and the safety and efficacy of a second course of RT is not well defined, technical and planning features are yet to be clarified. In this study, we compared various treatment planning systems (TPS) used in RT in a patient who had progressed meningioma after three applications of Gammaknife radiosurgery (GK-SRS). Case Presentation: 55-year-old male patient was diagnosed with grade-1 meningioma of the sphenoid wing in 2014 and subtotal excision was performed, with no further treatment. Progression was detected in 2016, and 11 Gy single fraction GK-SRS was applied in two sessions (inferior and superior parts of the tumor was irradiated in separate GK-SRS applications with 2 months apart) to the recurrent lesion in the right spheno-orbital region in a GK center. Patient was well until June 2022 when progression was detected in the right infratemporal region. Another GK-SRS application of 11 Gy was performed to the patient at the same institute.In April 2023 progression of the tumor was detected, tumor was irresectable and patient referred to our department for fractionated radiotherapy. Recurrent tumor was originating from right sfenoid wing and extending to right infratemporal fossa. We obtained the radiation dose distributions from the previous GK-SRS plans. Due to dose limits on the right optic nerve due to previous radiation dose disturbution , the conventional fractionated radiotherapy was planned . The PTV dose was planned to be 45 Gy/25 fx. Eclipse and Brainlab systems were compared for treatment planning. Right optic nerve dose of EQD2 was already above the limits, thus conventional fractionation (45 Gyin 25 fractions) was prescribed. Two separate plans were generated using Varian-Eclipse and Brainlab-Elements TPS, and the dose distribution of those plans were compared. Plan optimization was performed in both planning systems to provide PTV D%95. While the PTV Dmax was 57.24 Gy in BrainLAB, it was 48.7 Gy in Eclipse. Dmax doses for Brainlab and Eclipse were: right optic nerve 10.11 Gy vs. 26.9 Gy, chiasm 6.68 Gy vs. 20.5 Gy respectively. In Eclipse plan optimization, the collimator and table angles were optimized manually, while in Brainlab planning system, they were automatically handled, therefore normal tissues can be better preserved with increase of hot spots inside the PTV. This situation is observed clearly in this case. CONCLUSION Using different table and collimator angles in plan optimization can yield better results in providing normal tissue dose tolerance, especially in the irradiation of central nervous system.
OS03.6.A UNSUPERVISED CLUSTERING OF MORPHOLOGY PATTERNS ON WHOLE SLIDE IMAGES GUIDE PROGNOSTIC STRATIFICATION OF GLIOBLASTOMA PATIENTS
Authors: B Baheti, S Innani, M P Nasrallah, S Bakas
Journal: Neuro-Oncology (2023)

Abstract BACKGROUND Glioblastoma is the most common malignant adult brain tumor with a poor prognosis and heterogeneous morphology. Stratifying glioblastoma patients according to overall survival (OS) from H&amp;E-stained histopathology whole slide images (WSI) using advanced computational methods is a challenging task with direct clinical implications. We hypothesize that quantifying morphology patterns present in WSI can yield biomarkers of prognostic relevance contributing to optimizing clinical decision-making. MATERIAL AND METHODS This work is based on 188 glioblastoma (IDH-wt, grade 4) cases identified in the TCGA-GBM and TCGA-LGG, based on the 2021 WHO classification criteria. One Diagnostic WSI from each patient at 10X magnification was selected (ntraining/nhold-out-test =152 /36) and labeled as short (&amp;lt;9 months, n=94) or long (&amp;gt;13 months, n=94) survivors. The WSI is split into non-overlapping 256x256 patches, and extensive patch-level WSI curation is conducted to discard artifactual content, i.e., glass reflections, pen markings, black lines on the slide, and tissue tearing. Each patch is described by a feature vector of 512 dimensions using a pre-trained VGG16. Principal component analysis reduced the dimensionality of these vectors to 236 such that 85% variance is retained. Unsupervised k-means clustering revealed distinct groups of morphology patterns, where the number of clusters is automatically determined based on the rand index and silhouette coefficient. The proportions of these patterns describe the tumor’s spatial heterogeneity and are used to distinguish between short and long survivors using a random forest classifier. RESULTS We identified seven clusters of distinct morphology patterns, including 3 categories of tumor cellularity (low/intermediate/high), necrosis/macrophages, and other prognostically-relevant characteristics. The patient-level short vs long survivor prediction is driven by the proportion of these patterns present in WSI achieving classification accuracy, sensitivity and specificity of 83.83%, 94.44%, and 72.72% respectively on the hold-out test set. The high sensitivity signifies the algorithm’s ability to accurately predict the short survivors which is important in treatment planning and patient management. CONCLUSION The interpretability analysis of various morphologic patterns in distinct histologic sub-regions of glioblastoma may uncover correlations with short and long survivors, providing a deeper understanding of the complex relationship between histologic features and clinical outcomes and shedding light on the heterogeneity of glioblastoma. This association could offer additional prognostic information to clinical neuropathologists during microscopic assessment, leading to more refined prognostication and potentially impacting clinical decision-making for improved patient outcomes.
P06.15.B IMMUNOTHERAPEUTIC TARGETING OF FIBROBLAST ACTIVATION PROTEIN (FAP) IN TREATMENT REFRACTORY GLIOBLASTOMA USING NOVEL CAR-T CELL THERAPY
Authors: N Tatari, H Mohamed Seid Hedad, A Zingg, E M Bartoszek, V Tschan, T Schenker, M Ritz, P Miletic, C Venugopal, M Etter, S K Singh, H Läubli, G Hutter
Journal: Neuro-Oncology (2023)

Abstract BACKGROUND Glioblastoma (GBM) is the most common malignant primary adult brain tumor, characterized by extensive cellular and genetic heterogeneity. The Standard of Care (SOC) therapy and clinical trials have not been successful in improving patients’ survival which underscores an urgent need for developing new effective therapies for this treatment refractory disease. MATERIAL AND METHODS In silico and in vitro analysis have revealed high level of Fibroblast Activation Protein (FAP) expression in GBM tissue in multiple cell populations including endothelial cells, fibroblasts, stromal cells and tumor cells, but not on normal brain tissue, making FAP a safe and suitable therapeutic target as it allows for destruction of tumor cells as well as effective elimination of their supporting microenvironment. As Chimeric antigen receptor (CAR) expressing T cells have shown promising results against multiple cancers in the past few years, we aimed to target FAP in GBM by FAP specific CAR-T cells generated using a novel GMP-ready FAP-CAR construct produced based on a virus-free CAR gene transfer using advanced sleeping beauty transposon technology and preclinically test their anti-tumor efficacy against GBM at in vitro and in vivo level. RESULTS Our data revealed that co-culturing CAR-T cells with FAP+ GBM cells (U87) results in increased surface expression of T-cell activation markers. Moreover, FAP CAR-T mediated cytotoxicity against FAP+ GBM cells was also observed in the co-culture of GBM and CAR-T cells. For further validation, the effect of FAP CAR-T cells will be tested on patient-derived GBM organoids. The in vivo efficacy of FAP CAR-T cells is currently under investigation and we anticipate that the treatment of GBM tumor-bearing mice with FAP CAR-Ts results in extended survival and reductions of tumor burden. CONCLUSION These rigorously obtained data show high level of efficacy for FAP-specific CAR-T cells against GBM suggesting that clinical development of this therapeutic modality can provide a novel therapeutic strategy for GBM patients that can be used in combination with SOC or other immunotherapeutics. Therefore, upon successful completion of the preclinical study, we plan to conduct a phase I dose-escalation trial of autologous FAP-CAR T cells for patients with recurrent Glioblastoma.
P11.22.B ANALYSIS OF FACTORS RELATED TO POSTOPERATIVE RECURRENCE AND PROGNOSIS ABOUT HIGH GRADE SPINAL CORD GLIOMAS
Authors: W Guihuai, G Chuntian, J Linkai, Y Beibei
Journal: Neuro-Oncology (2023)

Abstract BACKGROUND High grade spinal glioma (HGSG), an extremely rare tumor, accounts for about 7-30% of spinal glioma. Its incidence is only 0.22/100000. The tumor has a rapid clinical progression and a poor prognosis, with a median survival time of 12-24 months. In previous studies on the prognosis of HGSG, the factors related to the prognosis are quite different due to inconsistent tumor classification and diagnosis criteria. It is rarer in the study of postoperative recurrence. Therefore, various factors limit the clinician’s judgment on the factors related to the recurrence and prognosis of HGSG after surgery. MATERIAL AND METHODS In this study, the clinical data of 44 patients who were pathologically diagnosed with HGSG and admitted to the Department of Neurosurgery of Beijing Tsinghua Changgung Memorial Hospital from January 1, 2015 to January 1, 2020 were retrospectively analyzed. The postoperative recurrence and death were considered as the research end time, the individual characteristics, imaging characteristics, pathological characteristics, age in treatment, gender, McCormick score, tumor location, WHO grade, tumor volume, degree of resection, radiotherapy, chemotherapy, and H3K27M expression, Ki-67 index, and P53 expression were included in the COX regression model for the univariate and multivariate analysis. The factors related to the recurrence and prognosis of HGSG after surgery were further explored. RESULTS The median recurrence-free duration of 44 patients with HGSG was 13.0 months, and the recurrence-free rates of 6 months and 1 year after surgery were 75.0% and 51.9%; the median survival time of the enrolled patients was 21.0 months. The multivariate COX regression analysis on the recurrence of HGSG after surgery showed that the risk of the recurrence was higher in the III-IV group than that the I-II group for the McCormick score ( p=0.001). For WHO grade, the risk of the recurrence was higher in the IV group than that in the III group (p=0.029). The multivariate COX regression analysis on that survival after HGSG surgery showed that the risk of the death was higher in the III-IV group than that in the I-II group for the McCormick score (p=0.006), and the risk of the death was higher for the tumor in the cervical segment than that in the cervical thoracic segment ( p=0.005), thoracic segment ( p=0.003), thoracolumbar segment ( p=0.011). The risk of the death was higher in the H3K27M positive group ( p=0.014) than that in the H3K27M negative group. 0.049). CONCLUSION HGSG, as a highly malignant tumour, exhibits rapid progression even after surgical treatment. For future post-operative recurrence and prognosis determination of HGSG, there is a need to focus on assessing the preoperative spinal cord functional status, tumour location, WHO classification and H3K27M mutation status to assist clinicians in giving the best treatment plan.
P13.16.A MACHINE LEARNING-BASED RADIOMIC MODEL USING MULTIPARAMETRIC MAGNETIC RESONANCE IMAGING FOR PREDICTION OF POSTOPERATIVE VISUAL RECOVERY OF PITUITARY ADENOMA PATIENTS
Authors: Y Zhang, C Chen, J Xu
Journal: Neuro-Oncology (2023)

Abstract BACKGROUND Preoperative prediction of the visual outcome after pituitary adenoma surgery is crucial to clinical decision-making but remains challenging. We aimed to develop radiomic models based on multiparametric magnetic resonance imaging (MRI) to predict the postoperative visual outcome for pituitary adenoma patients using machine learning approaches. MATERIAL AND METHODS A cohort of 152 patients who underwent endoscopic endonasal transsphenoidal surgery of pituitary adenomas were retrospectively enrolled and divided into the recovery group and the non-recovery group based on the six-month postoperative visual examinations. Radiomic features of the optic chiasm were extracted from preoperative T1-weighted imaging (T1WI), T2-weighted imaging (T2WI) and contrast-enhanced T1-weighted imaging (T1CE), respectively. Predictive models were constructed by least absolute shrinkage and selection operator wrapped with support vector machine through the five-fold cross-validation in the development cohort, and then evaluated in the independent test cohort. Area under the receiver operating characteristic curve (AUC), accuracy, specificity and sensitivity were used to assess the predictive performance of models. RESULTS A total of four predictive models were established based on selected radiomic features from three sequences individually or in combinations. Three features from T1WI, two features from T2WI and nine features from T1CE were selected in the multiparametric radiomic model that represented the best performances among the four models, with AUC values of 0.851 (95% CI: 0.768 - 0.933) in the development cohort and 0.847 (95% CI: 0.722 - 0.971) in the independent test cohort. CONCLUSION Our proposed machine learning-based radiomic model using multiparametric MRI can be utilized to assist in predicting the postoperative visual recovery of pituitary adenoma patients in clinical practice.
P10.20.B POSTOPERATIVE ISCHEMIA CAUSED BY MICROSURGICAL RESECTION PROMOTES PRONEURAL-TO-MESENCHYMAL TRANSITION IN GLIOBLASTOMA
Authors: A Ballestín, C Pichol-Thievend, G Bourmeau, B Blanchard, A Pettiwala, J Reveilles, S Leboucher, O Anezo, G Seano
Journal: Neuro-Oncology (2023)

Abstract BACKGROUND Four glioblastoma (GB) cellular states drive the intratumoral heterogeneity of this lethal primary brain tumor and are influenced by genetics, the tumor microenvironment (TME), and response to treatment. The impact of microsurgical resection on the TME and plasticity of GB cells is unknown. Postoperative cerebral ischemic events have been described after these surgical resections, altering the proper distribution of subsequent chemo-radiotherapy treatment. Despite the aggressive standard of care, 90% of patients experience recurrence a few months after treatment and it usually begins with the regrowth of highly invasive cells that spread from the peritumoral brain resection zone. Therefore, the objective of this study was to perform morphological and transcriptomic phenotyping of residual tumor cells and TME after microsurgical resection. MATERIAL AND METHODS The GFP-transduced syngeneic GB IDH-wildtype cell lines CT2A and GL261 were orthotopically implanted in C57Bl6j mice brains. We developed a refined microsurgical resection protocol for GB in a size-matched study by carefully following the same surgical steps performed in patients. Mice were randomly divided into four groups: control (prior to surgery) and 1, 3, and 7 days post-surgery. Tumor tissues were harvested for time-resolved bulk and single-cell RNA sequencing as well as immunohistochemistry (IHC) studies. RESULTS According to our time-resolved transcriptomic and IHC analyses, microsurgical resection induced pronounced proneural-to-mesenchymal transition (PMT), chromatin remodeling, and stimulation of hypoxia-driven pathways in residual GB cells after surgery. Moreover, single-cell RNA-seq of post-resection tumors allowed us to observe significant changes in the TME relative to the immune response and vascular function in line with ischemia exposure. CONCLUSION The impact of microsurgical resection has important consequences on the phenotypic landscape of GB tumor cells and TME, which is characterized by a transient ischemic TME that induces PMT in GB cells. In addition, we developed a refined microsurgical resection model that can be useful in a wide variety of preclinical studies. Support/Disclosure: This study was supported by the Institut National du Cancer (INCa; 1154 INCa-2020-1-PLBIO-01-ICR-1) and by the Marie Skłodowska-Curie Postdoctoral Fellowship under the European Union’s programme Horizon2020 (HORIZON-MSCA-2021-PF-01, GlioSurg, Grant agreement ID: 101061921).
P19.05.A THE NEURONAL CORRELATES OF BRAIN TUMOR ASSOCIATED SEIZURES IN HUMAN AND MOUSE PERITUMORAL CORTEX
Authors: A Bolleboom, B L J Bouwen, C M F Dirven, A J P E Vincent, Z Gao
Journal: Neuro-Oncology (2023)

Abstract BACKGROUND The occurrence of seizures is the most common comorbidity in malignant brain tumors. Recent advancements in the field of cancer neuroscience indicate that seizures can potentially influence brain tumor progression through intricate neuron-glioma interactions in the peritumoral infiltrated cortex of glioma patients. Therefore, understanding not only the tumor processes but also the neuronal properties in the tumor microenvironment could provide key insights into the relationship between epilepsy and tumor progression. To investigate this, we conducted a study to characterize neuronal alterations in glioma infiltrated neocortex of both patients and a glioma mouse model. MATERIAL AND METHODS Infiltrated peritumoral cortex was obtained from both epileptic and non-epileptic patients undergoing brain tumor surgery. Ex vivo brain slices were prepared and single-cell electrophysiology was performed on peritumoral neurons. High grade gliomas were induced into compound LoxP-conditional mice via stereotactic viral injection in combination with serial electro-corticographic activity to monitor epileptogenesis. RESULTS Ex vivo recordings from infiltrated human peritumoral cortex revealed electrophysiological and morphological alterations in neocortical neurons of patients experiencing seizures. Using an inducible immunocompetent high-grade glioma mouse model, we tracked the progression of cortical epileptogenesis during tumor infiltration. We observed several spatial and temporal changes in the peritumoral cortex of glioma mice, including progressive glial reaction and gradual neuronal reduction. We also identified intrinsic and network alterations in the cortical neurons of glioma mouse model, consistent with the electrophysiological characteristics of human peritumoral cortex prior to seizure onset. CONCLUSION Overall, our study demonstrated dynamic electrophysiological and histological changes in human and mouse peritumoral cortex during the course of tumor progression and epileptogenesis. These findings provide important insights into brain tumor associated seizures and cast light on new therapeutical targets for treatments.